statistic Definition and Topics - 41 Discussions

A statistic (singular) or sample statistic is any quantity computed from values in a sample that is used for a statistical purpose. Statistical purposes include estimating a population parameter, describing a sample, or evaluating a hypothesis. The average (aka mean) of sample values is a statistic. The term statistic is used both for the function and for the value of the function on a given sample. When a statistic is being used for a specific purpose, it may be referred to by a name indicating its purpose.
When a statistic is used to estimate a population parameter, the statistic is called an estimator. A population parameter is any characteristic of a population under study, but when it is not feasible to directly measure the value of a population parameter, statistical methods are used to infer the likely value of the parameter on the basis of a statistic computed from a sample taken from the population. For example, the mean of a sample is an unbiased estimator of the population mean. This means that the expected value of the sample mean equals the true mean of the population.In descriptive statistics, a descriptive statistic is used to describe the sample data in some useful way. In statistical hypothesis testing, a test statistic is used to test a hypothesis. Note that a single statistic can be used for multiple purposes – for example the sample mean can be used to estimate the population mean, to describe a sample data set, or to test a hypothesis.

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  1. F

    A Computing a variance in astrophysics context

    Below the error on photometric galaxy clustering under the form of covariance : $$ \Delta C_{i j}^{A B}(\ell)=\sqrt{\frac{2}{(2 \ell+1) f_{\mathrm{sky}} \Delta \ell}}\left[C_{i j}^{A B}(\ell)+N_{i j}^{A B}(\ell)\right] $$ where ##_{\text {sky }}## is the fraction of surveyed sky and ##A, B##...
  2. B

    Bayes' theorem and disease prevalence

    Hello at all! I have to solve this exercise: A tampon diagnostic test provides 1% positive results. The positive predictive values (probabilities of positive test disease) and negative (absence disease given negative test) are respectively 0.95 and 0.98. What is the prevalence of the disease...
  3. Amy_93

    I Statistic uncertainties in cross section plots - how to calculate?

    Hi there, I hope I chose the right forum for my question. So, basically, I'm doing an analysis measuring the number of signal particles in a certain momentum bin i, and doing two corrections: Nsig, i=M*(Nmeas, i-Nbkg, i) Here, M is a matrix covering PID correction and PID efficiencies, and...
  4. gind_id


    for reference you can see JS in lognormdist use by call : formulajs.LOGNORMDIST(value, mean, stdev, true) logpearsondist use by call : formulajs.NORMSDIST(z, true) anybody can help?
  5. TheBigDig

    Sum of the Expected Values of Two Discrete Random Variables

    Apologies if this isn't the right forum for this. In my stats homework we have to prove that the expected value of aX and bY is aE[X]+bE[Y] where X and Y are random variables and a and b are constants. I have come across this proof but I'm a little rusty with summations. How is the jump from the...
  6. U

    I Conditional distribution of geometric series

    Can someone help me on this question? I'm finding a very strange probability distribution. Question: Suppose that x_1 and x_2 are independent with x_1 ~ geometric(p) and x_2 ~ geometric (1-p). That's x_1 has geometric distribution with parameter p and x_2 has geometric distribution with...
  7. Conservation

    I Nonparametric Hypothesis Tests

    Hello everyone, Say you have two sample distributions that are known to be two different distributions (one randomly drawn from a Poisson distribution, other randomly drawn from an uniform distribution). Given that you know the distributions are not going to be normal, a two-sample t-test would...
  8. P

    Frequency Table

    is the most common size 6 , is my taking right, if not please provide explanation please
  9. A

    I Statistics proof: y = k x holds for a data set

    Simple linear regression statistics: If I have a linear relation (or wish to prove such a relation): y = k x where k = constant. I have a set of n experimental data points ...(y0, x0), (y1, x1)... measured with some error estimates. Is there some way to present how well the n data points shows...
  10. C

    Two teams, A and B, are playing a series of games

    My attempt I used negative binomial to solve the problem, however I'm left with a polynomial that is difficult to solve? Is there any other way to approach this problem? I used the inequality because I'm trying to find the range of p. Since the probability of winning the series for team...
  11. A

    I Discrete to continuum Gaussian function

    I have a question regarding a paragraph in "Radiation detection and measurement" by Knoll. In the chapter about the discrete Gaussian it states that "Because the mean value of the distribution ##\bar{x}## is large , values of ##P(x)## for adjacent values of x are not greatly different from each...
  12. A

    I Poisson error bar in a histogram from a MonteCarlo simulation of collisions between particles at LHC

    Hello everybody, I need a help, primarly a confirmation about my reasoning. I have data from a MonteCarlo simulation of collisions between particles at LHC (made with Madgraph). I have plotted some variables, for example the angle between two final leptons. Then I have normalized the plot to a...
  13. D

    A Estimation error from estimation quantile of normal distribution

    Hi guys, For my (master) project I am trying to find the probability that a random variable, which is normally distributed, exceeds a quantile that is estimated by a limited number of observations. See attached for my attempt. - Is it correct? - How to incorporate the fact that the mean and...
  14. Jarvis323

    A Similarity between -/+ weighted distributions

    Suppose that you have +/- elements aggregated into a weighted distribution function that represents some deviation from an unknown background distribution. What would be a good similarity metric for comparing two such distributions (2D or 3D), if they each represent different perturbations...
  15. Jakub

    I Small Reduced Chi Squared interpretation

    Hello everyone, I would be happy if someone explained the small reduced chi squared value to me. I have fitted a set of measured data with an exponential function, which I need for some sw calculations. The fit seams great, the origin sw also provides the reduced chi squared, but it is very...
  16. R

    Bayesian Probability Distributions

    Hi, I was having some trouble doing some bayesian probability problems and was wondering if I could get any help. I think I was able to get the first two but am confused on the last. If someone could please check my work to make sure I am correct and help me on the last question that would be...
  17. R

    Conceptual Question regarding hypothesis testing regression

    Homework Statement Hi, I had a question regarding testing a regression models coefficients. Say there is a regression model that has the form: y = b0 + b1x1 + b2x2 + b3x3 + b4x4 + e For the sake of simplicity let: e be the random error, x1 is age, x2 is severity, and x3 is anxiety. y is...
  18. L

    I Problems that could occur in estimating n from a Binomial distribution

    Hi, I am doing the following question: I have estimated both n and theta. But the part that is throwing me off is what problem could you encounter in estimating n here? My only idea is that it might be something to do with the sample...
  19. D

    I How does the distribution depend on a variable resolution

    Dear all, We were trying to solve the following question but did not quite understand what to do. The question is as follows: The reconstructed invariant mass is usually described by a Gaussian (or Normal) distribution. However, the resolution σ (the width of the distribution) is found to...
  20. G

    Minimize the sum of Type I and Type II errors

    Homework Statement Given X_1,\dots,X_n a simple random sample with normal variables (\mu, \sigma^2). We assume \mu is known but \sigma^2 is unknown. The hypothesis is \begin{cases} H_0: & \mu=\mu_0 \\ H_1: & \mu=\mu_1 > \mu_0 \end{cases} Determine the rejection region R...
  21. R

    Confusion between z and t values

    Homework Statement Hi, Alright so I have some confusion on when to use specific tests and the z vs t test. Given this example (not my homework) could someone please clarify. Alright say you have a random sample of size 200. You find the sample mean to be 10 and the sample standard deviation...
  22. R

    Help on determining independent events

    Homework Statement Hi, I have this question that I've been pondering for a while, I keep flipflopping on what I think is right. I only need help on the last part on whether the events are independent or not, the rest of the text is backstory to the question. I know for events to be independent...
  23. D

    Probability theory and statistics for Robotics and ME

    I study control theory and robotics. Recently I figured out that I have a much deeper understanding of probability and statistics compared to my colleagues. Is this 'talent' valuable in my field and if so, where? We used this theory to define white noise, but nothing of now. Also I am...
  24. R

    Chi-square goodness of fit cannot find expected values

    Homework Statement An article in Business Week reports profits and losses of firms by industry. A random sample of 100 firms is selected, and for each firm in the sample, we record whether the company made money or lost money, and whether or not the firm is a service company. The data are...
  25. T

    I What is Yates' correction of contingency?

    I can't understand a word of's_correction_for_continuity']Wikipedia.[/PLAIN] [Broken] P.S. What I know so far is subtracting 0.5 from O-E if df=1 in Goodness of fit (?) is Yates' correction.
  26. T

    I Level of significance and acceptance and rejection of the null hypothesis

    Why do we reject the null hypothesis in Goodness of fit when the Chi square statistic is less than the tabulated value of chi-square at say 5% level of significance and accept when it is more? What does it mean to have a Chi-square value more or less than the value assigned to a certain level...
  27. T

    I Understanding the null hypothesis

    I was reading Bio-statistics principles and practice by Antonisamy and stumbled upon the following: Null hypothesis is a hypothesis that suggests an absence of difference, association or effect, the negation of which provides evidence for presence of difference, association or effect. The only...
  28. T

    Maximum likelihood of a statistical model

    Homework Statement I look at the distribution ##(Y_1,Y_2,...,Y_n)## where ##Y_i=μ+(1+φ x_i)+ε_i## where ##-1<φ<1## and ##-1<x_i<1## . x's are known numbers. ε's are independent and normally distributed with mean 0 and variance 1. I need to find the the maximum likelihood estimator for μ and...
  29. N

    Energy in a crystal

    Hello, I am stuck at the beginning of an exercise because I have some trouble to understand how are the energy level in this problem : In a crystal we have Ni2+ ions that we consider independent and they are submitted to an axial symmetry potential. Each ion acts as a free spin S=1. We have the...
  30. V

    A What is first and Second order Dependence?

    Can someone please explain to me what it means what they say a model is "first and second order dependence?"